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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Hash Hashemian: Visionary leadership
As Dr. Hashem M. “Hash” Hashemian prepares to step into his term as President of the American Nuclear Society, he is clear that he wants to make the most of this unique moment.
A groundswell in public approval of nuclear is finding a home in growing governmental support that is backed by a tailwind of technological innovation. “Now is a good time to be in nuclear,” Hashemian said, as he explained the criticality of this moment and what he hoped to accomplish as president.
Rong Kong, Jerome Spanier
Nuclear Science and Engineering | Volume 168 | Number 3 | July 2011 | Pages 197-225
Technical Paper | Geometric Convergence of Adaptive Monte Carlo Algorithms for Radiative Transport Problems Based on Importance Sampling Methods | doi.org/10.13182/NSE10-29
Articles are hosted by Taylor and Francis Online.
Importance sampling is a very well-known variance-reducing technique used in Monte Carlo simulations of radiative transport. It involves a distortion of the physical (analog) transition probabilities with the goal of causing events of interest in the computation to occur more frequently than in the analog process. This distortion is then compensated by a corresponding alteration of the estimating random variable in order to remove any bias from the estimates of quantities of interest. In this paper, we construct several families of estimators based on importance sampling methods to solve general transport problems and prove that the adaptive application of each estimator produces geometric convergence of the approximate solution. We also present numerical results that illustrate important elements of the theory.